Kroonen AI / Lab engagements

Deep technical work for teams that need to own the system.

We partner with a small number of teams to build, train, and stress-test AI systems around real privacy, infrastructure, and product constraints.

Request a fit check See what we’ve built

Capabilities / 01-03

Three ways we do deep work.

Each lane is scoped around a decision or working outcome. Product subscriptions and support stay on their own product pages.

01 Build

Ship an AI product, not an integration demo.

We design agent workflows, private interfaces, communications systems, and the infrastructure that keeps them useful in production.

Useful when

You know the outcome, but the system crosses product, model, data, and infrastructure boundaries.

Scope can include

Agent runtimes, tools, permissions, and orchestration
Self-hosted or hybrid inference, RAG, and private interfaces
Web, mobile, voice/SMS, and operational workflows
MCP servers, provider adapters, and existing-system integrations

You receive

Architecture and decision record
Working implementation and deployment
Tests, documentation, and operational runbook
Clean handoff to your team

Lab proof Libre Claw · Libre Phone · Libre WebUI

02 Train

Adapt the model only when the product needs it.

We handle data, fine-tuning, evaluation, and from-scratch training when prompting an API no longer solves the real problem.

Useful when

The product needs behavior, cost, latency, language coverage, or ownership that an off-the-shelf endpoint cannot provide.

Scope can include

Feasibility, architecture, and model selection
Dataset curation, deduplication, and synthetic data
Fine-tuning and distributed model training
Capability, behavioral, and domain evaluation

You receive

Reproducible data and training recipe
Checkpoints and inference package
Evaluation report and known limitations
Deployment and iteration plan

Lab proof Genesis 1B · 80,000 steps · 2× RTX 4090

03 Stress-test

Find the failure path before deployment does.

We test models and agent systems where prompts, tools, permissions, and sensitive data meet, then turn the findings into concrete engineering work.

Useful when

Your model or agent can reach tools, private context, external systems, or users who will behave unpredictably.

Scope can include

Prompt injection, jailbreaks, and system-prompt leakage
Tool misuse, permission abuse, and data-exfiltration paths
Behavioral drift and domain-specific evaluation
Agent boundaries, provider fallbacks, and failure recovery

You receive

Threat model and prioritized test plan
Reproducible evaluation suite
Risk-ranked findings and evidence
Remediation plan and retest

Typical artifact Threat model · Eval suite · Remediation record

Lab proof / Built here

We build before we advise.

These are lab products and research programs, not borrowed case studies or anonymous client claims.

Explore the complete portfolio

01 Train Genesis 1B 1B parameters · 80,000 steps · 2× RTX 4090 02 Build Libre Claw Permissioned tools · local memory · multi-provider 03 Build Libre Phone Voice · SMS/MMS · IVR · Cloudflare Workers

Ways to work / Clear start, clean handoff

Choose the smallest useful engagement.

The commercial shape follows the work: fixed scope for a diagnostic, milestones for a build, or reserved capacity for ongoing R&D.

01 Fixed scope

Technical diagnostic

One hard product, architecture, model, or risk question. We reduce the uncertainty before anyone commits to a larger build.

Output

Decision memo, system or risk map, and a scoped next move.

02 Milestone-based

Focused build

A working system or clearly defined model/evaluation milestone, built with visible technical checkpoints.

Output

Working artifact, tests, documentation, deployment, and handoff.

03 Reserved capacity

Embedded lab

Ongoing iteration for programs where research, product, and operations need to stay tightly coupled.

Output

Continuous builds and evaluations with a direct working cadence.

Frame

Name the constraint and the decision it blocks.

Prove

Retire the hardest technical risk first.

Build

Turn the evidence into a working system.

Transfer

Leave code, tests, docs, and ownership behind.

Direct technical access

The people scoping the system are the people building it.

Artifacts over theater

Working code, evaluations, and decisions, not recurring slide decks.

Handoff without lock-in

Source, documentation, and operational knowledge move with your team.

Fit check / Direct to the lab

Start with the constraint.

In a few sentences, tell us what must remain private, what needs to ship, and what you have already tried.

01The decision or outcome you need

02The hardest technical constraint

03Any timeline or operational boundary

Prefer a direct note?

[email protected]+1 (916) 999-5979